Returns the batched diagonal part of a batched tensor.
tf.raw_ops.MatrixDiagPartV3( input, k, padding_value, align='RIGHT_LEFT', name=None )
Returns a tensor with the k[0]
-th to k[1]
-th diagonals of the batched input
.
Assume input
has r
dimensions [I, J, ..., L, M, N]
. Let max_diag_len
be the maximum length among all diagonals to be extracted, max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))
Let num_diags
be the number of diagonals to extract, num_diags = k[1] - k[0] + 1
.
If num_diags == 1
, the output tensor is of rank r - 1
with shape [I, J, ..., L, max_diag_len]
and values:
diagonal[i, j, ..., l, n] = input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N, padding_value ; otherwise.
where y = max(-k[1], 0)
, x = max(k[1], 0)
.
Otherwise, the output tensor has rank r
with dimensions [I, J, ..., L, num_diags, max_diag_len]
with values:
diagonal[i, j, ..., l, m, n] = input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N, padding_value ; otherwise.
where d = k[1] - m
, y = max(-d, 0) - offset
, and x = max(d, 0) - offset
.
offset
is zero except when the alignment of the diagonal is to the right.
offset = max_diag_len - diag_len(d) ; if (`align` in {RIGHT_LEFT, RIGHT_RIGHT} and `d >= 0`) or (`align` in {LEFT_RIGHT, RIGHT_RIGHT} and `d <= 0`) 0 ; otherwise
where diag_len(d) = min(cols - max(d, 0), rows + min(d, 0))
.
The input must be at least a matrix.
input = np.array([[[1, 2, 3, 4], # Input shape: (2, 3, 4) [5, 6, 7, 8], [9, 8, 7, 6]], [[5, 4, 3, 2], [1, 2, 3, 4], [5, 6, 7, 8]]]) # A main diagonal from each batch. tf.matrix_diag_part(input) ==> [[1, 6, 7], # Output shape: (2, 3) [5, 2, 7]] # A superdiagonal from each batch. tf.matrix_diag_part(input, k = 1) ==> [[2, 7, 6], # Output shape: (2, 3) [4, 3, 8]] # A band from each batch. tf.matrix_diag_part(input, k = (-1, 2)) ==> [[[0, 3, 8], # Output shape: (2, 4, 3) [2, 7, 6], [1, 6, 7], [5, 8, 0]], [[0, 3, 4], [4, 3, 8], [5, 2, 7], [1, 6, 0]]] # LEFT_RIGHT alignment. tf.matrix_diag_part(input, k = (-1, 2), align="LEFT_RIGHT") ==> [[[3, 8, 0], # Output shape: (2, 4, 3) [2, 7, 6], [1, 6, 7], [0, 5, 8]], [[3, 4, 0], [4, 3, 8], [5, 2, 7], [0, 1, 6]]] # max_diag_len can be shorter than the main diagonal. tf.matrix_diag_part(input, k = (-2, -1)) ==> [[[5, 8], [9, 0]], [[1, 6], [5, 0]]] # padding_value = 9 tf.matrix_diag_part(input, k = (1, 3), padding_value = 9) ==> [[[9, 9, 4], # Output shape: (2, 3, 3) [9, 3, 8], [2, 7, 6]], [[9, 9, 2], [9, 3, 4], [4, 3, 8]]]
Args | |
---|---|
input | A Tensor . Rank r tensor where r >= 2 . |
k | A Tensor of type int32 . Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main diagonal, and negative value means subdiagonals. k can be a single integer (for a single diagonal) or a pair of integers specifying the low and high ends of a matrix band. k[0] must not be larger than k[1] . |
padding_value | A Tensor . Must have the same type as input . The value to fill the area outside the specified diagonal band with. Default is 0. |
align | An optional string from: "LEFT_RIGHT", "RIGHT_LEFT", "LEFT_LEFT", "RIGHT_RIGHT" . Defaults to "RIGHT_LEFT" . Some diagonals are shorter than max_diag_len and need to be padded. align is a string specifying how superdiagonals and subdiagonals should be aligned, respectively. There are four possible alignments: "RIGHT_LEFT" (default), "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals to the right (left-pads the row) and subdiagonals to the left (right-pads the row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is the opposite alignment. |
name | A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as input . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/MatrixDiagPartV3